An Overview, Challenges, and Future Directions - SAMSI

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Experiments Models Connectivity Prediction Summary Comparative Analysis Simulation Results: awFC versus Standard (Unweighted) Clustering Table: Percent accuracies and standard errors (in parentheses). G=13 clusters used for all results, and σ 2 set using the experimental data. Noise-level Accuracy awFC Unweighted σ 2 Overall 97.35 (1.02) 94.61 (1.59) In-network 89.74 (4.61) 76.82 (7.78) Cross-network 98.70 (0.58) 97.78 (0.72) 1.25σ 2 Overall 96.72 (1.15) 93.28 (1.73) In-network 87.01 (5.46) 70.60 (8.48) Cross-network 98.46 (0.61) 97.32 (0.80) 1.50σ 2 Overall 96.13 (1.29) 92.33 (1.77) In-network 84.38 (6.01) 66.28 (8.52) Cross-network 98.23 (0.67) 96.97 (0.84) F. D. Bowman (Emory University) SAMSI: NDA RTP, NC 55 / 77
Experiments Models Connectivity Prediction Summary Other Connectivity Methods Model-based methods (Bayesian): Chen et al., 2013, submitted. Xue and Bowman, 2013, submitted. Patel et al., 2006a, Human Brain Mapping. Patel et al., 2006b, Human Brain Mapping. Whole-brain complex networks (graph theoretic methods) Simpson et al., 2013, Statistics Surveys. Effective Connectivity Granger causality Structural equation modeling Dynamic causal modeling F. D. Bowman (Emory University) SAMSI: NDA RTP, NC 56 / 77
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An Overview, Challenges, and Future Directions - SAMSI

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